Study on the Careers of MIT Mechanical Engineering
Undergraduate Alumni
ARCHIVES
MASSACH LISET- INSTITr TE
OF rECHNOLOLGY
by
Kelly Wang
JUN 2 4 2015
Submitted to the
Department of Mechanical Engineering
in Partial Fulfillment of the Requirements for the Degree of
LIBRARIES
Bachelor of Science in Mechanical Engineering
at the
Massachusetts Institute of Technology
June 2015
2015 Massachusetts Institute of Technology.
All rights reserved.
Signature redacted
Signature of Author:
Departf4ent of Mechanical Engineering
May 8, 2015
'/,
Certified by:
_Signature redacted
Warren Seering
Weber-Shaughness Professor of Mechanical Engineering
Thesis Supervisor
Signature redacted
Accepted by:
Anette Hosoi
Professor of Mechanical Engineering
Undergraduate Officer
Study on the Careers of MIT Mechanical Engineering
Undergraduate Alumni
by
Kelly Wang
Submitted to the Department of Mechanical Engineering
on May 8, 2015 in Partial Fulfillment of the
Requirements for the Degree of
Bachelor of Science in Mechanical Engineering
ABSTRACT:
The purpose of this study is to understand the skills used in the professional field in
order to tailor the MIT undergraduate curriculum to address those needs. Data was
collected through a survey sent to the graduating classes of 1992 through 1996,
2003 through 2007, and 2009 through 2013 in order to get a range of responses.
The survey focused on topics pertaining to technical knowledge, engineering skills,
work environment skills, and professional attributes. The questions focused on
frequency of use, expected proficiency, and source of knowledge of these topics.
Results of the data were categorized by frequency, proficiency, and source, as well
as by occupation and graduating year.
Responses show a lower frequency of use for the technical reasoning knowledge
and a high frequency of use for communication-based skills. However, this is
because technical knowledge is considered valuable to a specialized group of
people, whereas the work environment skills are more career-independent.
One method of addressing this observation is to balance out the number of lecturebased classes and project-based classes.
Additional interpretations of the data, along with their implications on the
curriculum, are discussed in more detail.
Thesis Supervisor: Warren Seering
Title: Weber-Shaughness Professor of Mechanical Engineering
2
Special Thanks to:
Joseph Seering, Jagruti Patel, the Office of Institutional Research, the MIT Mechanical
Engineering department for their help with the creation and distribution of the
survey.
Professor Warren Seering for his enthusiasm and support in making this study
possible in addition to his incredible insight on the project based on previous
studies.
3
Table of Contents
Chapter 1: Introduction
1.1 Goals of the Study
1.2 Background
1.3 Previous Research
6
6
6
6
Chapter 2: The Survey
2.1 The Foundation
2.2 Modifications to the Survey
2.3 Distributingthe Survey
7
7
9
12
Chapter 3: Data Analysis and Interpretations
3.1 Frequency of Use
3.2 Expected Proficiency
3.3 Sources of Knowledge and Skills
3.4 Occupation Comparisons
3.5 CareerPaths
13
13
16
17
20
26
Chapter 4: Data Interpretationsand Implications
4.1 Data Interpretation
4.2 Implications on the Curriculum
4.3 Curriculum Modificationsand Additions: A PersonalOpinion
4.4 FutureSteps
4.5 Conclusion
29
29
30
31
33
34
Chapter 5: Appendices
35
Chapter 6: References
49
4
List of Figures
Figure 1: Source of Knowledge Conditional Logic
Figure2: Frequency of Use Bar Chart
Figure3: Expected Proficiency Bar Chart
Figure 4: Primary Source Bar Chart
Figure 5: Primary and Secondary Sources Bar Chart
Figure 6: Current Occupation by Graduating Year
Figure 7: Roles of Engineers and Managers
Figure8: Frequency of Use by Occupation
Figure9: Tasks: Engineers, Managers, and Other
Figure 10: First Occupation by Graduating Year
Figure 11: First Occupation by Graduating Year- Recoded
Figure 12: Number of Companies by Graduating Year
Figure 13: Number of Years at Current Company by Graduating Year
Figure 14: Modified Primary Source Bar Chart
10
14
16
18
19
21
21
22
23
26
27
28
29
32
List of Tables
Table 1: Occupation Comparisons- Engineers and Managers
Table 2: Tasks: Engineers, Managers, and Other
Table 3: Open-ended Response Frequencies
5
20
25
30
Chapter 1: Introduction
Goals of the Study
The objective of this study is to gather information on the professional skills of the
MIT Mechanical Engineering alumni in order to understand the knowledge and
skills utilized in the workplace.
The gathered information is then analyzed in order to better understand the
important skills needed in the professional field as well as common career paths.
The purpose of this study is to apply this information towards the Mechanical
Engineering curriculum, so that the knowledge and skills taught in the
undergraduate coursework accurately reflect the needs of professionals in similar
careers. Additionally, this information will be extremely relevant for current
mechanical engineering undergraduates as they start their personal career paths.
We intend to make this information easily accessible to current undergraduates in
the hope that they can make more informed decisions about their own career
directions and better understand the specific tasks that certain careers entail.
Background
In 2004, Kristen Wolfe focused her undergraduate thesis on the knowledge and
skills of MIT Mechanical Engineering alumni, entitled "Understanding the Careers of
the Alumni of the MIT Mechanical Engineering Department". In this study, Kristen
Wolfe and her thesis advisor Professor Warren Seering collected data from the
graduating classes of 1992 through 1996, inquiring about the knowledge and skills
utilized in their professions. The data was divided into four categories: technical
knowledge and reasoning, personal and professional skills and attributes,
interpersonal skills, and engineering skills. Alumni were asked about expected
proficiency, frequency of use, and source of knowledge for each of these categories.
Kristen observed a low frequency of use and expected proficiency in the technical
areas of knowledge, while teamwork and communication were most commonly
used. Through these observations, Kristen suggested an integration of these skills
into the core requirements. For more information on Kristen Wolfe's thesis, see
Appendix 1.
This study follows Kristen's research method closely in the hopes of confirming the
implications of her findings. In addition, one of the goals of this study was to learn
about the career paths of alumni over time, further understanding the evolution of
their roles in the workplace as well as the type of tasks they perform on a daily
basis.
Previous Research
On top of Kristen Wolfe's research, there have been several other studies focused on
the curriculum and career paths. In 2003, Catherine Kelly studied the career paths
that MIT undergraduates pursued over a span of 35 years entitled "Some Trends in
the Career Paths Followed by Alumni of the MIT Mechanical Engineering
6
Department". In Catherine's study, which surveyed the graduating classes of 1967
to 2002, she concluded that approximately two-thirds of each graduating class
becomes engineers and managers. As the number of years since graduation
increases, the percentage of engineers decreases while the percentage of managers
increases.
In 2010, Neha Batra focused on the career paths of alumni, and how their
undergraduate experience prepared them for their jobs. In her study, entitled "A
Look to the Future: MIT Alumni and their Course 2 and 2-A Educational Experience",
Neha compared the preparedness of those who graduated with a Course 2 degree
with those who graduated with a Course 2-A degree. In a survey sent out to the
graduating classes of 1999-2009, Neha asked about the importance and how well
MIT prepared them in specific skills. Similar to Kristen's conclusions, Neha observed
an emphasis on the communication and leadership skills, whereas the technical and
economic skills were the least important.
Chapter 2: The Survey
The Foundation
The foundation of the research method was based on the 2004 survey that Kristen
Wolfe developed in her study. Wolfe's survey, which was based on previous
research done by Professor Edward Crawley in the department of Aeronautics and
Astronautics, divided the knowledge and skills in question into four categories:
technical knowledge and reasoning, personal and professional skills and attributes,
interpersonal skills, and engineering skills. Each of these categories was then
subcategorized further into topics: the technical knowledge and reasoning section
focused on the topics covered in the required classes for a mechanical engineering
degree, while the remaining three categories were largely based on Prof. Crawley's
previous research, entitled "The CDIO Syllabus: A Statement of Goals for the
Undergraduate Engineering Education". The format created by Wolfe can be seen
below:
1) Technical Knowledge and Reasoning
a. Underlying Sciences
b. Underlying Mathematics
c. Mechanics of Solids
d. Mechanical Behavior of Materials
e. System Dynamics and Control
f. Dynamics
g. Fluid Mechanics
h. Thermodynamics
i. Heat Transfer
j. Engineering Design Process
k. Manufacturing
2) Personal and Profession Skills and Attributes
a. Engineering Reasoning and Problem Solving
b. Experimentation and Knowledge Discovery
c. System Thinking
7
3)
4)
d. Personal Skills and Attributes
e. Professional Skills and Attributes
f. Independent Thinking
Interpersonal Skills
a. Teamwork
b. Communication
Engineering Skills
a. External and Societal Context
b. Enterprise and Business Context
c. Market Context
d. Developing an Idea
e. Designing
f. Testing
For each of these topics, Wolfe focused on the expected proficiency, the frequency of
use, and the source of knowledge. The scales used for each of these questions were:
Expected Proficiency
- To have experienced or been exposed to
- To be able to participate in and contribute to
- To be able to understand and explain
- To be skills in the practice or implementation of
- To be able to lead or innovate in
Frequency of Use
Never
Hardly ever- a few times a year
- Occasionally- at least once a month
Regularly- at least weekly
Frequently- on most days
Pervasively- for almost everything I do
Source
-
-
U- Undergraduate Program at MIT
G- Graduate School
J- Job
E- Somewhere Else
N- Did Not Learn
For further details on the survey that Wolfe sent in her study, please see Appendix 2.
The rationale behind keeping the majority of the 2004 survey intact was so that we
would have the opportunity to compare the data between Wolfe's survey and the
new survey. With these intentions in mind, the exact scales were used for the
expected proficiency and frequency of use portions of the survey. Additionally, the
topics and were taken directly from the 2004 survey, with some minor changes.
8
Modifications to the Survey
There were a few changes made based on feedback and discussions with the Office
of Institutional Research and beta testers. One noticeable change was the recategorization of the subject blocks. The Technical Knowledge category stayed
relatively untouched, with the exception of the merging of System Dynamics and
Control and Dynamics into System Dynamics in part le. The rest of the blocks were
reorganized, however the topics themselves still remained the same. This was done
to increase understandability while still keeping the fundamental questions the
same for comparison purposes. For example, the Engineering Skills category was
moved immediately after the Technical Knowledge block to create a more fluid
structure. Within this block, the topics of Engineering Reasoning, Experimentation,
and System Thinking were added. In addition, the topic of leadership was added
under the Work Environment section. We found it important to distinguish the skill
of leadership from teamwork, as the MIT undergraduate program has been putting
significant effort into developing these skills in programs such as the Undergraduate
Practice Opportunities Program (UPOP) and the Gordon-MIT Engineering
Leadership (GEL) program.
A full list of the changes can be seen below, marked with an asterisk (*). It is noted
that because of the reorganization of the questions, order effects would need to be
taken into account for any variation in the results. When discussing results, I will
refer back to these subject blocks, as they provide a structure for the twenty-five
individual topics.
1)
Technical Knowledge
a. Underlying Sciences
b. Underlying Mathematics
c. Mechanics of Solids
d. Mechanical Behavior of
Materials
e. System Dynamics*
f. Fluid Mechanics
g. Thermodynamics
h. Heat Transfer
i. Engineering Design Process
j. Manufacturing
2) Engineering Skills*
a. Engineering Reasoning*
b. Experimentation*
c. System Thinking*
d. Idea Development
e. Designing
f. Testing
3) Work Environment*
a. Independent Thinking*
b. Teamwork
c. Leadership*
d. Communication
4) Professional Skills and Attributes*
a. Personal Skills
b. Professional Attributes
c. External and Societal
Context*
d. Business Context*
e. Market Context*
Each of these topics included a short description in order to ensure that the
respondents' interpretations were similar. A detailed list of the topics and their
descriptions can be found in Appendix 3.
Learning from the 2004 survey, the source question was altered in order to get a
more meaningful response. In order to reduce the length of the survey and to
9
eliminate any irrelevant questions, a conditional logic was added to the source
question. Since we were only interested in the source of knowledge if the individual
used the skill frequently, the source question was only asked for the topics where
the respondent answered At Least Once a Week, On Most Days, and ForAlmost
Everything I Do. Therefore, the Did Not Learn option was removed from the
multiple-choice selection. To achieve a higher level of detail, theJob option was split
into two in order to distinguish a formal training program from an informal on-thejob project. We were interested in further understanding the methods that people
learned certain skills: whether it was from a structured class setting or hands-on
experience. The modified list of options was chosen to be:
Source
-
Undergraduate Program at MIT
Graduate Program
Company-Sponsored Training Program*
Work Experience*
-
Elsewhere
Also based on feedback from past surveys and alumni, the option of a secondary
source response was added. A screenshot of the conditional logic and the survey
layout can be seen below.
Where did you gain your knowledge or skills?
How often do you use particular technical knowledge or
skills?
categlory.
Never
Underlying Sciences
Phtysics, Chemistry Biology
0
0
At
Least
Once a
Month
0
At
Least
Once a
Week
0
On
Most
Days
0
For
Almost
Everything
I Do
0
Underlying Mathematics
Calculus, Linear Algebra,Differential
Equations;Staristics
0
0
0
0
0
0
Mechanics of Solids
Force and Moment Equilibrium;
Conditions of Geomretric Fit
0
0
S
0
0
0
Mechanical Behavior of Materials
Elasticity Fracture, Fatigue, Plasticity
Friction; Use of Materials in
Mechanical Design
0
0
0
S
0
0
System Dynamica
Dynamic Modeling and Response,
System Functions Kinematics of
Bodies in Motion; Frequency
Response; Lnearized Models
your primary
0
0
0
0
0
Undergraduate
Program at
Graduate
MIT
Program
CompanySponsored
Training
Program
Expenence
Elsewhere
8
8:
Work
Primary
8
a8
D
aI
Secondary 1.1
applicable)
n
E
a8
El
System Dynamics
Dynamic Modeling and Response; System Functions;1Onematics of Bodies In Motion;
FrequencyResponse; Unearized Models
Primary
0
rank
and secondary sources.
Mechanical Behavior of Materials
Elsatciy Fracture; Faigue; Plasticlty Friction; Use of Materials In Mechanical Design
TECHNICAL KNOWLEDGE
A Few
Times
a Year
lect the best option to describe where you gained the maority of yor
understandling In the following categories. If there Is more than one source, please
Please
Please select the option to describe how often you use the knowledge or ldills from each
Secondary (i
applicable)
Unde rgraduate
Pr gram at
Mi1t
Graduate
Program
CompanySponsored
Training
Program
Work
Eaperice
Elsewhere
1
8:
8
E]
8
L1
0
0
0
Figure 1: Source of Knowledge Conditional Logic. For topics where At Least Once a Week, On
Most Days, or ForAlmost Everything I Do were chosen (L), source of knowledge was asked
(R).
At the end of Wolfe's survey, the person was asked to specify their current
occupation. They could self-categorize themselves as an engineer, a manager, a
consultant, etc. A full list of occupations can be found in Appendix 4. However, in
order to get a more detailed description of a person's occupation, this question was
10
also significantly modified. In an attempt to find the best approach to this common
question, I looked at past alumni surveys sent by the Office of Institutional Research
to the MIT alumni. Looking at the surveys sent out institute-wide in 2005, 2009, and
2013 (alumni surveys are sent out every four years) the occupation question was
differently phrased and laid out every time, thereby confirming that there is not a
straightforward way to ask the simple question. There were some slight
modifications and additions to the occupation list, which can be found in Appendix
5. For the purposes of this survey, the focus was to further categorize the engineers,
managers, and consultants, as those were the most commonly chosen answers in
previous results. In order to do this, another conditional logic was added.
If Engineeror Managerwas selected as a person's occupation, then the next question
asked about the person's primary area, and the following list was presented:
-
Manufacturing
Software
Engineering Systems
Product Design and Development
Technical Support
-
Research
Facilities
-
-
Quality
-
-
Project Manager
Program Manager
Business Development
Marketing and Sales
Finance
Engineering Manager
Executive
Other- Please Specify
If Consultantwas selected as a person's occupation, then the next question asked
about the person's primary role:
-
Engineering Consultant
Management Consultant
Financial Consultant
-
Medical Consultant
Other- Please Specify
These subcategories were compiled from a variety of public lists on the most
popular areas of mechanical engineering and consulting. Because a large portion of
alumni become technical managers and some project managers identify as
engineers, the follow-up question for engineers and managers was combined into
one.
In addition to the current occupation question set, each person was also asked about
his or her first occupation after graduating with a Bachelor of Science from MIT.
Same as CurrentOccupation was added to the list of answers, while Doctor, Attorney,
and Professorwere removed from the list. The same conditional logic described
above was added after this question as well. If Same as CurrentOccupation was
selected, the respondent skipped any follow-up questions on specific roles,
regardless of their current occupation. The combination of these two responses was
used to get a brief glimpse at our alumni's various career paths and how they
changed over time. To further elaborate on an individual's career path, every
individual was asked how many companies they have worked at, the number of
years spent at their current company and what further degrees they received. These
11
questions were asked in order to get a sense of the geographical stability of a certain
type of career path as well as further education required.
Another addition to the survey was focused on the specific tasks that a person
performs on a weekly basis to answer the age-old question, "What does an engineer
do during a typical week?" There were three main categories: Communicating and
Interacting, Planningand Designing, and Creatingor Modifying. The individual was
asked to select all the tasks that they spent more than five hours on during the past
week. A full list of the tasks can be found in Appendix 6.
Lastly, at the end of the survey, people were left with open-ended questions to leave
any last remarks. There were three questions asked, with text box answers. They
were:
- "What aspects in your MIT experience have been most valuable to you
professionally?"
- "If applicable, how did your college internships influence your career
decision?"
- "Faculty from the MIT Schools of Engineering and Management are
considering the possibility of offering continuing professional education
opportunities for alumni, in formats including online classes, resident short
courses, and degree programs. If MIT were to offer courses such as these,
what topics would you like to see included?"
The survey underwent multiple revisions before reaching its final state. Feedback
was taken from Professor Seering, the Office of Institutional Research, and the
Leaders in Global Operations (LGO) community. The survey was beta-tested in
order to confirm readability and to get a reasonable estimate of the time required to
take the survey. The comments and suggestions from these different perspectives
helped create a comprehensive and succinct final survey. A complete copy of the
final survey sent can be seen in Appendix 7.
Distributing the Survey
The survey was sent out through the Office of Institutional Research to all of the MIT
Mechanical Engineering alumni in the graduating classes of 1992 to 1996, 2003 to
2007, and 2009 to 2013. These three ranges were chosen because we wanted to
look at the evolution of responses of graduates approximately 5, 10, and 20 years
out of college. Note that the 1992 to 1996 graduating classes are the same group of
people that Wolfe reached out to in her survey, and the 2003 to 2007 graduating
classes are the equivalent age group that Wolfe focused on in her study. In total, the
survey reached approximately 1800 individuals by email on March 27, 2015. Those
who didn't respond within a week and a half were sent a follow-up reminder email.
A final third reminder was sent out three weeks later as a last effort to get as many
responses as possible. As of May 7, 2015, 768 people responded to the survey,
resulting in a 42.7% response rate. Please note that the third wave of responses are
not fully included in this analysis plots due to time constraints, however 583 filled
out the survey after the first reminder email, a 32.4% response rate. Therefore
12
conclusions can be drawn from the 583 responses that provide a basic
generalization of the population. The third wave of responses was kept for future
research in the topic. The content of the email correspondence can be found in
Appendix 8.
Chapter 3: Data Analysis and Interpretations
In this next chapter, I will go through the results that I found particularly relevant
from the survey responses, represented through graphs and charts plotted in Excel.
Please note that the following graphs serve only as a fraction of the many ways to
visualize the data. Because of the abundance of information gathered from the
survey and the time constraint of a thesis, there are additional observations that can
be drawn from the data that I will not cover, but I do hope that they will be covered
in future research. I will focus on the most interesting topics that I have found
during my analysis, as well as the most relevant correlations for the objective of this
thesis-the mechanical engineering department's curriculum. This data is meant to
serve as a stepping-stone for further investigation and discussion on the topic.
Throughout the analysis, I will include my own interpretation on the subject matter,
with the understanding that I am not an expert in the curriculum aside from my
personal experience as a student.
Using a program called Statistical Package for the Social Sciences (SPSS), I was able
to analyze the 583 responses more easily. The 'Crosstabs' function was used to find
the number of times a certain response was selected. Additionally, the responses
could be categorized by a respondent's graduating year or occupation, if needed.
The CSV files were then exported into Excel in order to obtain plots of the responses.
Frequency of Use
First looking at frequency of use, I found the frequencies of each response using
SPSS. Exporting the table into Excel and plotting it in a stacked bar graph, the
following graph was generated. The bar graph is done in percentages in order to
normalize the different categories, since the total number of responses varied
slightly (from 542 to 550 responses). On the left hand side, the topics are sorted by a
cumulative sum of the At Least Once a Week, On Most Days, and For Almost
Everything I Do responses, in descending order. This was chosen to be the cutoff
since the conditional logic for the source question focused on these three responses.
However, one could choose to include the At Least Once a Month response in the
cumulative sum, and the topics would only move slightly-up or down by a
maximum of three (and that occurs only once: Testing moves up by three). The first
two topics, PersonalSkills and Independent Thinking, would remain the same. The
number inside each bar represents the number of responses for each respective
question.
13
As seen in the chart, the most frequently used skills are:
1. Personal Skills
2. Independent Thinking
3. Professional Attributes
4. Communication
5. Teamwork
6. Engineering Reasoning
7. Leadership
After these seven topics, there is a significant gap (approximately 25%) based on the
At Least Once a Month (Green) and At Least Once a Week (Purple) division. In these
top seven topics, all four of the Work Environment topics (Independent Thinking,
Teamwork, Leadership, and Communication) are included, as well as the Personal
Skills and ProfessionalAttributes portion of the Professional Skills and Attributes
subject block. According to the dictionary, knowledge is the theoretical or practical
understanding of a subject, while skills are the proficiencies developed through
training or experience. These most frequently used topics would be considered
skills as opposed to knowledge. Therefore they tend to be used more frequently, in
combination with the use of knowledge.
Frequency of Use
Personal Skills
Independent Thinking
Professional Attributes
Communication
Teamwork
Engineering Reasoning
Leadership
Idea Development
System Thinking
Business Context
Designing
Experimentation
Engineering Design Process
Market Context
External and Societal Context
Underlying Sciences
Testing
Manufacturing
Underlying Mathematics
Mechanical Behavior of Materials
Mechanics of Solids
System Dynamics
Heat Transfer
Fluid Mechanics
Thermodynamics
299
IN
I M
11
252
259
190
254
22
188
101
*353
94
109
-
3114
90
110
105
-136
-
AIIIIIIII
144-N
121
47
ININNIIIII
56
____________________
60
102
176
"a
125
215
__
I
__
33
E24
3
165
151
155
145
0%
10%
20%
40%
A Few Times a Year
0 Never
At Least Once a Week
30%
0
On
Most Days
5()%
U
60%
70%
80%
90%
At Least Once a Month
For Almost Everything I Do
Figure 2: Frequency of Use Bar Chart, most frequently used to least frequently used.
14
100%
The next subsection of topics that is frequently used includes:
8. Idea Development
9. System Thinking
10. Business Context
11. Designing
12. Experimentation
While the gap between EngineeringDesign Process and Market Context is not as
significant as before (approximately 7%), the gap between Experimentation and
Market Context is more noticeable (11%) and I have arbitrarily chosen to include
EngineeringDesign Processwith the third grouping.
This second grouping includes the majority of the Engineering Skills block (Idea
Development, System Thinking, Designing, and Experimentation),in addition to
Business Context. It is interesting to note that of the three remaining topics in the
Professional Attributes subject block (Business Context, Market Context, and External
and Societal Context) the Business Context is used significantly more than the other
two.
The rest of the topics can be divided once more:
13. Engineering Design Process
14. Market Context
15. External and Societal Context
16. Underlying Sciences
17. Testing
18. Manufacturing
19. Underlying Mathematics
20. Mechanical Behavior of Materials
21. Mechanics of Solids
22. System Dynamics
23. Heat Transfer
24. Fluid Mechanics
25. Thermodynamics
All ten topics of the Technical Knowledge subject block are included in this last half.
EngineeringDesign Process is the first Technical Knowledge topic to show up on the
rankings. Please note that, similar to Engineering Reasoning, Engineering Design
Process is the first of its subject block to appear on the list. Both are noticeably more
used than their counterparts. The description of EngineeringDesign Process
possesses similar attributes to the descriptions of both Designing and Testing, and
lies in between these two topics on the chart.
The four least frequently used topics are four of the more advanced technical topics,
corresponding to the higher-numbered Mechanical Engineering courses that MIT
15
students tend to take as an upperclassman (2.004 - 2.006). Meanwhile, the
Technical Knowledge topics in the third grouping correspond to the GIRs and the
first Mechanical Engineering courses that undergraduates typically take, because
they form the foundation for a solid mechanical engineering background. Therefore,
because the knowledge of the more advanced topics is more specialized, it is
understandable that they are used in more specialized jobs, where only a select few
use them frequently.
Expected Proficiency
The Expected Proficiency stacked bar chart was produced using the same method as
the Frequency of Use chart. On the left hand side, the topics are sorted by a
cumulative sum of the To be able to participateand contribute to, To be able to
understandand explain, To be skilled in the practiceand implementation of, and To be
able to innovate and lead in responses, in descending order. This cutoff was chosen
because all four of these responses implied a sufficient knowledge of the topic such
that the person was comfortable using the skill in practice. The top four topics,
Communication, Personal Skills, Independent Thinking, and Teamwork, differ by a
total of four responses.
Expected Proficiency
Communication
Personal Skills
Independent Thinking
Teamwork
Professional Attributes
Leadership
Engineering Reasoning
Idea Development
Experimentation
Designing
System Thinking
Business Context
Testing
Market Context
Engineering Design Process
External and Societal Context
Underlying Mathematics
Manufacturing
Underlying Sciences
Mechanics of Solids
Mechanical Behavior of Materials
System Dynamics
Heat Transfer
Fluid Mechanics
Thermodynamics
230
3S0
7
141
0%
10%
20%
30%
40%
50%
60%
70%
To essentially have no knowledge of
NTo have
To be able to participate in and contribute to
*To be able to understand and explain
W:
80%
90%
some experience or exposure in
To be skilled in the practice and implementation of * To be able to innovate and lead in
Figure 3: Expected Proficiency Bar Chart, sorted by most proficient to least proficient.
16
100%
Comparing the Frequency of Use and the Expected Proficiency graphs, a high
Frequency correlates to a high Expected Proficiency, as one would expect.
Quantitatively, the two scales are difficult to compare, since the frequency scale is
not linearly distributed while the proficiency scale has a more linear interval.
Qualitatively, however, the four groupings listed above in the frequency discussion
remain intact. The order within the groupings changes slightly, but does not differ
by more than four slots (again, Testing having the largest jump between proficiency
and frequency). In the Testing case, this larger gap can be justified because those
using the skill once a month should still be able to participate and contribute to the
process.
Due to this high correlation between the frequency of use and the expected
proficiency, the graphs in the following section will focus on the frequency of use in
more detail, using the assumption that the same analysis could be done of
proficiency with similar results.
It may be discouraging to see the technical knowledge on the lower half of both the
frequency and proficiency charts, however, these topics still form the foundation of
a lot of engineering work. Looking at the bottom four topics, which remain in the
same order in both the charts, around 18-30% use the skill at least once a month.
However, about 35-46% need to at least be able to participate and contribute in this
area of expertise. Overall, the technical knowledge and skills tend to be considered
valuable to a specialized group of people, whereas the work environment skills are
more career-independent.
Sources of Knowledge and Skills
The primary source graph was produced using the same method as the Frequency
of Use and the Expected Proficiency charts. The left hand column's order is identical
to the Frequency of Use graph, since the conditional logic of this question was based
on the frequency response. Note that because of the conditional logic added to the
question, the total number of responses for each question varies significantly
between topics.
The majority of the technical knowledge and skills were learned in large part in the
undergraduate MIT curriculum. With the exception of Manufacturing, all of the
Technical Knowledge topics had "Undergraduate Program at MIT" selected as the
primary source more than 50% of the time. In the Engineering Skills block, all topics
selected "Undergraduate Program at MIT" as their primary source at least 40% of
the time. The five most frequently used skills, PersonalSkills, Independent Thinking,
ProfessionalAttributes, Communication, and Teamwork, were largely learned in
either a previous work experience or elsewhere. Interestingly, less than 50% of the
primary sources for these five skills were learned in a formal learning
environment-the Undergraduate Program at MIT (shown in light blue), Graduate
Program (orange), or a Company-Sponsored Training Program (gray).
17
Primary Source
N Undergraduate Program at MIT
N Graduate Program
gCompany-Sponsored Training Program
Work Experience
U
Elsewhere
181
Personal Skills
Independent Thinking
Professional Attributes
Communication
Teamwork
Engineering Reasoning
Leadership
Idea Development
System Thinking
Business Context
Designing
Experimentation
Engineering Design
Market Context
External and Societal Context
Underlying Science
Testing
Manufacturing
Underlying Math
Mechanical Behavior of Materials
Mechanics of Solids
System Dynamics
Heat Transfer
Fluid Mechanics
Thermodynamics
205
U
138
2 14
244U
-
981
254
124
114
194
M
108
*s54
85
142-
89
U
94
23
I
10
8
%
5
6
21
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Figure 4: Primary Source Bar Chart, sorted by most frequently used to least frequently used.
It can be noted that there is a large proportion of responses that stated "Elsewhere"
as their primary source of knowledge for both ProfessionalAttributes and External
and Societal Context. This could imply that there was some ambiguity in these
topics, as the description of ProfessionalAttributes includes "Ethics; Integrity;
Continuous Learning" which could be hard to identify a primary source. Similarly,
External and Societal Context was described as "Responsibilities of Engineers on
Society; Global Perspective", which again might be difficult to identify a source for.
In an effort to keep these answers succinct, there was no textbox included in this
question. For future studies, this may be something to consider adding in order to
receive a more descriptive response.
Adding the secondary sources into the tally, the next chart is generated. Since it was
emphasized that a secondary source of knowledge should only be selected if
applicable, the variation in responses is even larger than the primary source plot.
About 69.6% of respondents selected a secondary source, with a standard deviation
of 6.7%.
18
With the inclusion of the secondary sources, the number of "Company-Sponsored
Training Program" responses tripled in size for all of the topics. As companysponsored training programs tend to be short-term classes tailored to teach a
specific task relevant to the individuals' area of work, it makes sense that these
programs are effective in teaching a skill. However due to its short duration, it may
not necessarily be considered a primary source, therefore the relative spike in
secondary source selection is understandable. This can be particularly seen in
Leadershipand the five most frequently used skills, as well as Business Context and
Market Context-skills that are used frequently in the workplace, therefore
companies target them for sponsored training programs.
Primary and Secondary Sources
ULtndergraduate Program at MIT
8 Graduate Program
Company-Sponsored Training Program
Work Experience
U Elsewhere
h4
314
Personal Skills
Independent Thinking
Professional Attributes
Communication
Teamwork
Engineering Reasoning
Leadership
Idea Development
System Thinking
Business Context
Designing
Experimentation
Engineering Design
Market Context
External and Societal Context
Underlying Science
Testing
Manufacturing
Underlying Math
Mechanical Behavior of Materials
Mechanics of Solids
System Dynamics
Heat Transfer
Fluid Mechanics
Thermodynamics
335
251
320
347
236
332
202
1.81
236
~1
184m
132
1611
182
97
39
13 7136U
26
M7
79
60K
311
18i
191
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Figure 5: Primary and Secondary Sources Bar Chart, sorted by most frequently used to least
frequently used.
Looking at the Technical Knowledge section, the percentage of both graduate
program-based knowledge and work experience-based knowledge increased
significantly, again with the exception of Manufacturing (where the percentage of
undergraduate program-based knowledge increased instead of decreased). This
could be an indication of continuous learning, with Underlying Science, Underlying
19
Math, and Mechanics of Solids seeing the largest changes (approximately a 27%
decrease in undergraduate program-based knowledge).
However, it is still the case that several categories are still largely learned in an
informal learning environment or elsewhere. These categories include Professional
Attributes, Communication, Teamwork, Leadership, Business Context, and Market
Context.
Occupation Comparisons
With all of the data from the survey, there are countless ways to look at the dataset
in more detail. First I chose to look at the distribution of occupations. By graduating
year, as the number of years since graduation increases the percentage of engineers
generally decreases and the percentage of managers tends to increase, in agreement
with Catherine Kelly's conclusion. The values below are given with a 95%
confidence interval.
Year Group
Graduating Year Range
1
2009-2013
%of Engineers
%of Managers
%of Engineers
and Managers
52.83
8.9%
8.8
6.0%
61.63%
2
2003-2007
35.29 4.5%
19.2 6.9%
54.49%
3
1992-1996
18.49 8.9%
30.3 8.4%
48.79%
Table 1: Occupation Comparisons- Engineers and Managers. Average taken over each
graduating year range.
Additionally, the number of individuals who listed "Student" as their current
occupation was highly concentrated in the recent graduate years. To see what
advanced degrees people are pursuing, or have received, please refer to Appendix 9.
Note that the sample size of each graduating class is small (ranging from 22 to 72
responses), so the standard deviations between the years will typically be higher
than usual.
20
Current Occupation by Graduating Year
" Consultant
Manager
* Attorney
Currently Out of the Work Force
* Engineer
* Doctor
Banking/Finance
Other
" Professor (College or University)
U Student
100%
--
90%
7
-
5
9
5
5
7
3
2
6
4
56
80%
70%
60%
-
14
50%
40%
30%
_10-
20%
10%
0%
"ti,
IIN
'IV
N
A
@
-
0
P x P;'15 P;V
-'q Nq Nq Nq
Figure 6: Current Occupation by Graduating Year.
Roles of Engineers and Managers
0.350
0.300
0.250
0.200
0.150
0.100
0.050
0.000
III I..'.
A cn-
U--Z
INN~
C
~
1 30,
e
Figure 7: Roles of Engineers and Managers.
Within the group of people who selected Engineer or Manager, the distribution of
role was as follows: Product Design and Development, Engineering Systems, Project
Manager, Manufacturing, Software, Research, Executive, etc. The distribution is
fairly even, with the exception of Product Design and Development.
21
The number of individuals who self-reported as "Other" is relatively high. These
responses included, but were not limited to, Business Development, Real Estate,
Small Business Owner, Military, and High School Teacher.
Because the occupations of the respondents were known, the frequency of use
questions could be further dissected by career. In order to create large enough
group sizes so that the analysis could be extrapolated onto the group as a whole, I
chose to focus on three main groups: Engineers, Managers, and Other. Note that this
Other category now includes Consultants, Doctors, Attorneys, Professors,
Banking/Finance, those Currently Out of the Work Force, Students, and the original
self-reported Others. In order to compare these three groups and plot the
differences, I took the mean and standard deviations of the Frequency question in
SPSS, mapping "0" to "Never", "1" to "A Few Times a Year, "2" to "At Least Once a
Month", and so on. As mentioned before, since the time scale was in no way linearly
distributed, the averages themselves do not represent anything. However, they do
provide a straightforward method of comparison between the three groups. In the
Technical Knowledge block engineers tend to use the topics more frequently than
managers, while in the Professional Attributes block managers tend to use the topics
more frequently than engineers. However, both engineers and managers use the
skills in the Engineering Skills block similarly. There are notable large differences in
Leadership, Communication, Business Context, and Market Context, with managers
using the skill much more frequently than engineers.
Frequency of Use by Occupation
5
E Other
0 Manager
N Engineer
4
3
- - - ----
2
1
0
0
.0
-kc p V!
Z! *
-
0-
b;4
eP
)
4,#
0
4
'000.
4'
e-,v
Sp
4p4 p
e
gF,
4
p
'OV
.0
0'.
0
e",
.
I-IZ ,
;$ e C, C4
C
,g
O'b. ew
4
A
V
0 = Never
1=
Few Times/Year
2 = At Least Once/Month
4 = On Most Days
5= For Almost Everything I Do
Figure 8: Frequency of Use by Occupation.
22
3 = At Least Once/Week
S - Xl
In the survey, individuals were asked to select all of the tasks that they spent more
than five hours on during the previous week. Splitting the responses up by the three
occupation groups and then arranging the tasks by the most frequently selected, the
following graphs were produced.
Tasks- Engineers
Meeting with your project team
Reading or sending email
Responding to requests or questions from others
Working alone to make project decisions
Modifying the design of an existing component
Creating or modifying a CAD representation
Documenting projects or outcomes
Meeting with other company employees or organization
Developing project strategy or direction
Designing or conducting performance tests or building testing
Communicating with vendors or suppliers
Conducting analyses of the physics of a product
Mining previous projects or reports for information
Writing code
Planning or organizing a person or team's activities
Reworking a project decision to compensate for a
Interacting with customers or users
Evaluating competitors' products
Planning a code-building cycle
Interviewing candidates
UE
0.1
0
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0.3
0.4
0.5
0.6
0.7
0.8
0.9
Tasks- Managers
Reading or sending email
Developing project strategy or direction
Responding to requests or questions from others
Meeting with your project team
Meeting with other company employees or organization
Planning or organizing a person or team's activities
Documenting projects or outcomes
Working alone to make project decisions
Communicating with vendors or suppliers
Interacting with customers or users
Reworking a project decision to compensate for a
Mining previous projects or reports for information
Interviewing candidates
Evaluating competitors' products
Conducting analyses of the physics of a product
Designing or conducting performance tests or building testing
Modifying the design of an existing component
Writing code
Planning a code-building cycle
Creating or modifying a CAD representation
7-z
ZZII
0.1
0
23
0.2
Tasks- Other
Reading or sending email
Responding to requests or questions from others
Meeting with your project team
Developing project strategy or direction
Working alone to make project decisions
Meeting with other company employees or organization
Planning or organizing a person or team's activities
Interacting with customers or users
Documenting projects or outcomes
Mining previous projects or reports for information
Writing code
Communicating with vendors or suppliers
Modifying the design of an existing component
Reworking a project decision to compensate for a
Evaluating competitors' products
Designing or conducting performance tests or building testing
Conducting analyses of the physics of a product
Creating or modifying a CAD representation
Planning a code-building cycle
Interviewing candidates
0.1
0
0.2
0.3
0.4
0.5
0.6
0.7
Figure 9: Tasks: Engineers, Managers, and Other. Sorted by most frequently selected
response.
24
0.8
0.9
Below is a compilation of the task rankings into a table, to better compare the
typical tasks of engineers, managers, and 'other'. Communicating and Interacting
tasks are underlined and orange, Planning and Designing tasks are italicized and
green, and Creating and Modifying tasks are in purple.
Engineers
Managers
Other
Meeting with one or more
members of your project team
Reading or sending email
Reading or sending email
Reading or sendig email
Responding to requests or
questions from others
Working alone to make project
Developing projectstrategy or
direction
Respondingto
rgquiests or
Responding to requests or
questions from others
questions from others
Meeting with one or more
members of your project team
with one or more
Developing project strategyor
Meeting
.
Modifying the design of an existig
component
members of your proect team
Meeting with other company
employees or organization
members
direction
Meeting with other coma ny
employees or organization
members
Creating or modifying a CAD
representation
Planning or organizing a person or
team's activities
Working alone to make project
decisions
Documenting projects or outcomes
Documenting projects or outcomes
team's activities
Working alone to make project
Interacting with customers or
decisions
users
Developing project strategyor
direction
Communicatingwith vendors or
suppli ers
Documenting projects or outcomes
Designing or conducting
performance tests or building
testing rigs
Interacting with customers or
users
Mining previous projects or reports
for information
Communicating with vendors or
decisions
Planning or organizing a person or
Meeting with
other
company
employees or organization
members
Mining previous projects or reports
suppliers
for information
Writing code
Conducting analyses of the physics
Reworking a project decision to
Communicating with vendors or
of a product
compensate for a
lers
suppliers
Modifying the design of an existing
for information
component
Writing code
Evalunting competitors'products
Reworking a project decision to
compensate for a
misunderstanding
Mining previous projects or reports
Planning or organizing a person or
team's activities
Reworking a project decision to
compensate for a
misunderstanding
customers or
Interacting with
a usts
users
L
5q
misunderstanding
Interviewing candidates
Conducting analyses of the physics
Evaluatingcompetitors'products
of a product
Conducting analyses of the physics
Modifying the design of an existing
alprout
of
en
Mdmpte
of a product
component
Designing or conducting
Designing or conducting
performance tests or building
performance tests or building
testing rigs
testing rigs
Evaluating competitors'products
Writing code
Creating or modifying a CAD
Planning a code-building cycle
Planninga code-building cycle
Planning a code-building cycle
Creating or modifying a CAD
representation
Interviewing candidates
Interviewin
candidates
___________________________representation
Table 2: Tasks: Engineers, Managers, and Other. Communicating and Interactingtasks are
underlined and orange, Planningand Designing tasks are italicized and green, and Creating
and Modifying tasks are in purple.
25
Career Paths
An area of high interest is the correlation of career-related questions based on
graduating year. In the survey, people were asked to select their first occupation
after graduating with a Bachelor of Science from MIT. They were given the
additional option to select "Same as current occupation", seen in green. As the
number of years since graduation increases, the number of people who currently
have the same occupation that they did immediately after college slowly diminishes.
A significant portion of alumni switch careers as they get older, either through
managerial promotions or intentional career changes.
First Occupation by Graduating Year
U
Engineer
Manager
0 Consultant
Out of the Work Force
0 Student
Other
* Same as current occupation
7
100%
90%
JIN
80%
70%
60%
50%
40%
20%
-
10%
-
30%
0%
-r
2013 2012 201 120102009
-r
2007 2006 2005 2004 2003
1996 1995 1994 1993 1992
Figure 10: First Occupation by Graduating Year.
Using the Transform function in SPSS, the value of this question was recoded if the
person responded with "Same as current occupation". This was done so that we
could directly compare the types of jobs that people took directly out of college with
the types of jobs that people currently have. The following graph was produced
using the recoded values.
26
First Occupation by Graduating Year-Recoded
" Engineer
* Professor (College or Un iversity)
" Student
Manager
N Doctor
Other
* Consultant
* Attorney
* Banking/Finance
Out of the Work Force
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2013 2012 2011 2010 2009
2007 2006 2005 2004 2003
1996 1995 1994 1993 1992
Figure 11: First Occupation by Graduating Year-Recoded. The responses in green above
(Figure 10) were recoded to the individual's current occupation.
Two direct career path-related questions were asked in the survey:
1. How many different companies have you been employed at full-time since
you received your Bachelor of Science from MIT?
e. 5
a. 1
f. 6-8
b. 2
g. 9-12
c. 3
h. 12+
d. 4
place of employment?
current
your
at
worked
2. How many years have you
g. 6-7 years
a. <1 year
h. 8-10 years
b. 1 year
i. 11-15 years
c. 2 years
16-20 years
j.
d. 3 years
k. 20+ years
e. 4 years
f. 5 years
The following boxplot charts were taken directly from SPSS, separated by
graduating year. The values for the range responses were calculated using the mean.
For the singular 12+ companies response, the value of 13 was assigned. In this
boxplot, the bolded line represents the median response value, the shaded box
represents the 25th to 75th percentile, and the vertical lines represent the minimum
and maximum values. The outliers are represented with circles and stars. Plotted as
a function of the number of years out of college, the following plot is obtained.
27
*
How many different companies have you been employed at full-time since you
received your Bachelor of Science from MIT?
12.00-
10.0000
9L
8.00*
0
ja
E
6.00-
4.00-
66;A 0
2.00-
.00A1
A
GraduatIng Year
Figure 12: Number of Companies by Graduating Year. The bolded line represents the
median value, the shaded box represents the 25th to 75th percentile, and the vertical lines
represent the minimum and maximum values. The outliers are represented with circles and
stars.
The values for the range responses were calculated using the mean. For the singular
12+ companies response, the value of 13 was assigned. In this boxplot, the bolded
line represents the median response value, the shaded box represents the 25th to
75th percentile, and the vertical lines represent the minimum and maximum values.
The outliers are represented with circles and stars. Plotted as a function of the
number of years out of college, the following plot is obtained.
28
How many years have you worked at your current place of employment?
20.00-
a.
E
0
15.00-
0
0
0
10.00
00
.0
E
5.00
.00
--
Graduating Year
Figure 13: Number of Years at Current Company by Graduating Year. The bolded line
represents the median value, the shaded box represents the 25th to 75th percentile, and the
vertical lines represent the minimum and maximum values. The outliers are represented
with circles and stars.
Again, the values for the range responses were calculated using the mean. For the
20+years responses, the value of 21 was assigned. Plotted as a function of the
number of years out of college, the above plot is obtained.
Due to the small sample size, the deviations in these averages are larger than
expected. With more data points, these deviations can be improved significantly.
Chapter 4: Data Interpretations and Implications
Data Interpretation
Through this survey's results, I believe that we can conclude areas of strength and
areas for improvement for the Mechanical Engineering curriculum. Again, I include
my personal opinions on the interpretation of the data with the complete
understanding that I am not an expert in the curriculum details aside from my
personal experience as a student.
In accordance with what Kristen concluded in her 2004 thesis, I believe that the MIT
curriculum does a great job with providing a solid foundation of technical
knowledge reasoning, as seen in the source tables. Furthermore, this solid
29
foundation is necessary for the types of careers that MIT alumni pursue, as seen in
the frequency and proficiency correlations-despite the fact that the technical
knowledge topics are least frequently used, alumni are still expected to be
comfortable with and able to contribute to the topic.
I also agree that from the implications of the frequency and primary source charts,
there is room for improvement in the topics pertaining to the work environment
and one's personal and professional skills. However, since the most effective way to
learn these skills stem from an informal learning environment such as work
experience, these skills cannot-and should not-be taught directly in classes.
Instead, they must be incorporated into the already existing course load. The
lecture-based style of the core technical classes, specifically 2.001-2.006, does not
address these skills, and therefore has the potential for integration.
Yet, I do believe that MIT's strength in teaching engineering reasoning and problem
solving also arises from the lecture-based style of the core technical classes. As
many people stated in the first open-ended question, problem solving and critical
thinking were huge takeaways from the undergraduate course load. Of the
responses received, at least 102 people mentioned the problem solving skills
learned from MIT, and 73 mentioned learning how to think critically and/or
analytically. It should not go unnoticed that these are also incredibly valuable skills
that cannot be taught directly in classes, therefore MIT has been very successful in
this incorporation into the curriculum.
According to the alumni, project-based classes (2.007-2.009) are particularly strong
classes. In the same open-ended question as above, at least 21 responses specifically
mentioned 2.007, 17 mentioned 2.008 and 70 mentioned 2.009 as being valuable
learning experiences. In the responses, these project-based classes effectively taught
important skills such as hands-on experience, teamwork, and leadership.
Class Mentioned
Core Classes
(GIRs, 2.001-2.006)
2.007
2.008
2.009
2.671
# of Times Mentioned I Specific Skills/Knowledge Learned
14
Technical Knowledge, Analytical
Thinking/Problem Solving
21
Prototyping, Hands-on Experience
17
Teamwork, Hands-on Experience
70
Teamwork, Design, Leadership
7
Documentation, Communication
Table 3: Open-ended Response Frequencies.
Implications on the Curriculum
There is a delicate balance of both the more rigid lecture-based structure and the
looser project-based classes, since both effectively teach very applicable, yet
different, skills. In order for the current curriculum to address the topics related to
work environment and one's personal and professional skills, I believe that the best
approach is not necessarily to modify the teaching style of the core technical classes,
30
2.001-2.006, but instead to balance out the number of lecture-based classes and
project-based classes.
To my knowledge, this is the one of the objectives for the new 2-A curriculum,
where students can choose shorter lecture-based technical classes so that they can
pursue classes in their specific interests. I agree that a similar modification should
be made to the Course2 curriculum-not to the same extent, but to an extent.
Similar to the old 2-A requirements, I think a possible approach would be to make
one of the technical second-level subjects (2.002, 2.004, 2.006) optional, thereby
creating space to add another required project-focused class. A detailed list of the
old 2-A requirements can be found in Appendix 10. Contrary to the old 2-A
curriculum, I believe that 2.008 should remain a required class, with some
modifications. Thoughts for this new project-focused class will be discussed later.
Curriculum Modifications and Additions: A Personal Opinion
In a slightly modified Primary Source chart, where the Elsewhere option is
completely removed for ambiguity purposes, there are six topics that stand out as
having surprisingly low undergraduate contributions:
-
Manufacturing
Teamwork
Business Context
Market Context
Communication
Leadership
31
Modified Primary Source
N Graduate Program
Work Experience
* Undergraduate Program at MIT
a Company-Sponsored Training Program
Personal Skills
Independent Thinking
Professional Attributes
Communication
Teamwork
Engineering Reasoning
Leadership
Idea Development
System Thinking
Business Context
Designing
Experimentation
Engineering Design
Market Context
External and Societal Context
Underlying Science
Testing
Manufacturing
Underlying Math
Mechanical Behavior of Materials
Mechanics of Solids
System Dynamics
Heat Transfer
Fluid Mechanics
Thermodynamics
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Figure 14: Modified Primary Source Bar Chart, where the Elsewhere responses were taken
out.
All of these topics have something in common-of the alumni who use these skills
more than once a week, less than 35% of them cite MIT's undergraduate program as
their primary source.
The first two topics, Manufacturingand Teamwork, are two main learning objectives
of 2.008.
From a reflection of my personal experience as a Course 2 undergraduate, I have
noticed certain strengths that I think could be applied further to other aspects of the
curriculum in order to progress. Firstly, I believe I have been very fortunate because
I have consistently had passionate and committed professors for the majority of my
core classes. Specifically, there are four classes that stand out, and I think they all
possess one key characteristic. These classes are:
- Measurement and Instrumentation (2.671)
- The Product Engineering Process (2.009)
- Physics I & 11 (8.01 & 8.02).
The key feature that I have observed is the continuity of faculty throughout the
years (again, to the extent of my knowledge). Having one consistent faculty member
teach the course ensures that the feedback given at the end of every semester is
seriously taken into consideration for the future semesters. Additionally, this
32
continuity of faculty members implies a high personal investment in the quality of
how the class is taught, which is incredibly useful for that class's development.
Please note that this is a one-way implication, and that there are numerous cases
where a faculty member invests a huge portion of their time to the improvement of
a class without teaching the class every semester.
I understand that for the technical core classes, the continuity of professors may be
difficult since they tend to have their own research on the side (again, this is a oneway generalization) and that it may be more difficult since 2.008 is taught every
semester. However, I believe that this feature could be feasibly applied to the 2.008
class structure with positive benefits.
Another interesting area of discussion would be to consider the integration of the
TEAL-style into the 2.008 class structure. The TEAL-style, which is used to teach
8.01 and 8.02, could potentially help increase the incorporation of teamwork and
communication.
With regard to my thoughts on a new required project-focused class, I believe that
this is the opportunity to add the topics of Business Context and Market Context
directly into the curriculum. Seeing their extremely low undergraduate numbers in
the Primary Source chart, I believe that they have great potential in the course load.
Between 40-50% of survey respondents use this knowledge on a weekly basis. It
can be seen that managers use these topics significantly more than engineers,
however, by their early 30s approximately 20% of MIT alumni become managers.
This fraction, seen in the previous table on page 16, increases to 30% by the early
40s-a significant portion of our alumni. This project-based class would most likely
indirectly incorporate the skills of Leadership, Teamwork, and Communication,
thereby addressing the rest of the topics where the undergraduate learning
contribution is noticeably low.
Through the responses received from this survey, it is clear that the Mechanical
Engineering department has effectively taught the skills that they focus on. I believe
that a slightly more balanced focus on both communication and technical skills
would be beneficial to graduates in their professional lives.
Future Steps
Due to time constraints and the multitude of data, there are several areas that did
not get covered but I think would benefit from further research. First and foremost,
with the third wave of additional responses after the second reminder was sent out,
the graphs above should all be reproduced with the entire dataset after the survey is
closed. Quick comparisons were made to confirm that nothing was significantly
changed with the new response set; therefore the above analysis is still valid.
However additional responses will significantly help with the small sample issue
that occurs in data analysis of the CareerPath section.
33
In terms of data comparison, I believe that a huge area of interest would be to delve
into the consistency between the 2004 survey responses and the 2015 responses.
The only categories that are directly comparable are the Frequency of Use and
Expected Proficiency questions, with the exception of the Dynamics and Leadership
topics, but the comparison of the two datasets would be extremely insightful. There
are two main comparisons that can be made:
1. A comparison of the 2004 responses with the middle year group (graduating
classes of 2003-2007) in order to look at alumni who are the equivalent age
group
2. A comparison of the 2004 responses with the third year group (graduating
classes of 1992-1996) in order to look at alumni who responded to both
surveys
There are also additional topics that I would have liked to investigate in the
Occupation Comparison section, but did not. One comparison I would have liked to
spend more time on is the number of companies that people have worked at relative
to the type of occupation they hold. I believe that this can tell a lot about the stability
of a job type: whether a specific occupation tends to be associated with frequent
company changes, etc. It is often said that consultants spend 2-5 years before
switching either their career or their place of employment. With the number of
responses who reported as consultants, this could be researched using data.
Another topic of interest in the Occupation Comparisonsection would be the recategorization of occupation by technical focus. I did not discuss the results of the
engineering, management, and consulting roles asked in the survey, but this could
easily add another level of analysis to Chapter 3. Finally, for a more accurate
representation of the data, it is recommended to do a manual re-categorization of
the self-reported "others" into the pre-sorted categories. Going through the list of
"other" descriptions, there were several people who identify as project managers
and product managers, which could have been added to the Manager category.
There are also several responses for Business Development, Real Estate, High School
Teacher, and Military, which could have been added as their own group. However,
this has a relatively small impact since the Other category was combined during
analysis.
Conclusion
The Mechanical Engineering Department has been actively refining their programs
in order to best suit the needs of their students, as seen by the recently remodeled
2-A curriculum. As such, I believe that there is much discussion about suggested
improvements to the original Course 2 curriculum, and my research is only a small
portion of the efforts going into this topic. I am sure that there is much debate about
potential changes, both in feasibility and in approach, and there may be many who
disagree with some things that I have said. My hope is that the data I have found will
encourage further discussion on the topic, as I know that the department is
constantly looking for ways that they can improve the preparedness of their alumni
to be successful in post-graduate life.
34
Appendices:
Appendix 1: Kristen Wolfe's Thesis
The figures below are taken directly from Kristen Wolfe's thesis, showing her
results on Frequency of Use, Expected Proficiency, Source, and Occupation. The
Frequency of Use and Expected Proficiency values were found using the average of
all the responses.
Mean Expected Proficiency and Frequency of Use
5
4
3
2
-g
0
0
Average Profiioercy4
M Average Frequency
Exped Prolciency: 0 To have essentially no knoviedge of, 1 To have expeuenced or been exposed to. To be able to particpate in and
inVale in
conrkbtf to, 3 To be able to wderstid and epak 4 To be sed in the pracice or irrpiemertation, 5 To be able to lead or
Frequency of Use: 0 Never, 1 Hardly ever - a fewtimes a ye, 2 Occasionly - at least once a month, 3 Regularty - at least weey
4 Frequenlty - on most days, 5 Pervasively - for most everytn I do
35
Source
lo00
80%
130%
40%
.
0%
.
.
.
.
.
.
.
N-I
.
.
20%
ll))
I
Z
0%
.9P
i~~\\
\lIf,
m Undegtaduate Progrum at MrT
M Grwadue School
0 Somewhre Else
0 Job
U Did Not LeamI
Survey Respondents
3W8
100%
64
50
48
58
61
5
7
001w
13
13
0 Student
* Not cu rentlenyed
8D% -J--
oufside the home
0 Member of the Mliary
9
-
60%
399
* Non-Academic Researcher
a Professor
4
_____
13
* Atksney
3
0 Doctor
-
40%
---
0 C"Menmant
EManiger
*Engiee
20% 4--
0%ALL
1992
1993
1995
1994
36
1996
Below is an excerpt from Kristen Wolfe's chapter on the interpretation of her data.
Instead, I believe the charts show a need for integration of other topics into the
existing core classes. My experiences in 2.001-6 have shown me that these
classes are largely or entirely content knowledge based. The emphasis, from my
viewpoint, is on knowing the material. I believe the department does a good job
of providing the students with a very broad range of technical knowledge and
reasoning. This is also evidenced on the source table with around 80% citing
MIT as the primary source of their knowledge in these areas.
One disconnect I see is in the area of engineering reasoning and problem
solving. Only 60% report their primary source as MIT. I assume that most
professors believe the problem sets they assign are addressing this area.
However, I'm not sure that is what students get out of such an exercise. I believe
that for students to effectively learn engineering reasoning and problem solving
they must be directly taught how in the class. As Prof. Seering pointed out in a
presentation to the Engineering Committee on Undergraduate Education, most
Professors cannot verbalize their problem solving method [9]. Yet students are
for the most part expected to figure it out on their own. I know from experience
that some do not figure it out and only learn to recognize patterns in problems
and map them onto other problems at test time. I believe this is an area that
needs to be given serious attention if students are to be successful in a real
world engineering environment.
Another disconnect I see is in the area of experimentation and knowledge
discovery. Less than 50% report their primary source as MIT. I assume that
most professors believe the labs are addressing this area. However, I do not
believe that students get this experience from the labs. The labs students are
given in the various course 2 classes have explicit set-ups and desired
outcomes. Students aren't so much discovering knowledge as they are following
a prescribed set of instructions. Real experimentation is being given a problem
or question and experimenting to discover the answer. It would be a challenging
thing to replicate in the class environment, but perhaps the only way to give
students the necessary background in experimentation and knowledge
discovery.
The largest disconnects are in the areas of personal skills, professional skills,
independent thinking, teamwork and communication. These areas received the
largest scores for proficiency and frequency and the lowest for learning at MIT.
Appendix 2: Kristen Wolfe's Survey
This section serves to show the order and format in which the questions were
asked. The full list of topics is not shown in full in the screenshot of the survey, but a
full list is provided in Chapter 2.
37
This survey enumerates various topics associated with engineering. Please rank
each topic according to the following three criteria:
1. Expected Proficiency
For people in your line of work and at the same stage as you are in your
career (8 to 12 years past the BS degree), how competent are they expected
to be in each of these areas? Please mark a number from 0-5 indicating the
necessary proficiency level in column 1:
0- To have essentially no knowledge of
1. To have experienced or been exposed to
2. To be able to participate in and contribute to
3. To be able to understand and explain
4. To be skilled in the practice or implementation of
5. To be able to lead or innovate in
2. Frequency of Use
In your present position, how frequently do you employ the knowledge and
skills from each of these areas? Please mark a number from 0-5 indicating
the frequency in column 2:
0. Never
1. Hardly ever - a few times a year
2. Occasionally - at least once a month
3. Regularly - at least weekly
4. Frequently - on most days
5. Pervasively - for most everything I do
3. Source of Your Knowledge
Where did you gain the most understanding about each topic? Please
mark a letter in column 3:
U - Undergraduate Program at MIT
G - Graduate School
J - Job
E - Somewhere Else
N - Did Not Learn
38
Please indicate your response for each topic in each of the three columns.
If one or more of the italicized subtopics is of particular importance in your work, please circle it.
If we have missed a topic or a subtopic that is particularly importaint please write it in.
I
TECHNICAL KNOWLEDGE AND REASONING
Proficiency
0-5
Frequency
0-5
Source
U,G,J,E,N
1.1 UNDERLYING SCIENCES
Physics; Chemistry; Biology
1.2 UNDERLYING MATHEMATICS
Calculus, LinearAlgebra; Differential Equations; Statistics
1.3 MECHANICS OF SOLIDS
Force and Moment Equilibrium; Condtons of Geometric
Fit, Material Behavior
1.4 MECHANICAL BEHAVIOR OF MATERIALS
Elasticity Fracture, Fatigue, Plasicity, Fnchon, Wear,
Corrosion; Use of Materials in Mechanical Design
1.5 SYSTEMS DYNAMICS
Dynamic Modeling and Response; System Funcions,
Pole-Zeros, and Their interpretation
1.6 DYNAMICS
Kinematicsand Dynamics of Bodies in Motion, Behavior of
Linearized Models: Natural Modes and Frequency
Response, Wave Transmission and Reflection
1.7 FLUID MECHANICS
Incompressible Flows, Equations of Fluid Motion
1.8 THERMODYNAMICS
1' and 2"d Laws; Pure Substance Models
1.9 ENGINEERNIG DESIGN PROCESS
Concept generation; Detail design Machine elements;
Scheduling of Design Achvites; Prototype Testing
1.10 MANUFACTURNIG
Manufacturing Processes; Systems; Equipment
Appendix 3: Frequency/Proficiency/Source Topics and their Descriptions
1) Technical Knowledge
a. Underlying Sciences: Physics; Chemistry; Biology
b. Underlying Mathematics: Calculus; Linear Algebra; Differential Equations;
Statistics
c. Mechanics of Solids: Force and Moment Equilibrium; Conditions of Geometric
Fit
d. Mechanical Behavior of Materials: Elasticity; Fracture; Fatigue; Plasticity;
Friction; Use of Materials in Mechanical Design
e. System Dynamics: Dynamic Modeling and Response; System Functions;
Kinematics of Bodies in Motion; Frequency Response; Linearized Models
f. Fluid Mechanics: Incompressible Flows; Equations of Fluid Motion
g. Thermodynamics: First and Second Laws; Pure Substance Model
39
Heat Transfer: Heat Conduction; Forced and Free Convection; Radiation;
Condensation; Boiling; Heat Exchanger Design
i. Engineering Design Process: Concept Generation; Detail Design; Machine
Elements; Prototyping
j. Manufacturing: Manufacturing Processes; Systems; Equipment
2) Engineering Skills
a. Engineering Reasoning: Problem Solving; Problem Identification; Modeling;
Quantitative Analysis
b. Experimentation: Hypothesis Formulation; Experimental Inquiry; Hypothesis
Test and Defense
c. System Thinking: Defining the System and its Interfaces; Interaction in
Systems
d. Idea Development: Setting System Goals and Requirements; Defining Product
Function; Modeling of System
e. Designing: Design Process; Conceptual Design; Trade-off Analysis; Detail
Design
f. Testing: Building a Prototype; Test; Verification and Validation
3) Work Environment
a. Independent Thinking: Setting Project Goals; Working Independently
b. Teamwork: Goal Setting; Scheduling
c. Leadership: Decision Making; Organization and Delegation; Negotiation;
Ability to Motivate Others; Risk Management
d. Communication: Written; Multimedia; Graphical; Oral Presentation;
Communication to those Outside the Field
4) Professional Skills and Attributes
a. Personal Skills: Willingness to Take Risks; Creative Thinking; Time and
Resource Management
b. Professional Attributes: Ethics; Integrity; Continuous Learning
c. External and Societal Context: Responsibilities of Engineers on Society; Global
Perspective
d. Business Context: Enterprise Strategy; Goals and Planning; Entrepreneurship;
Working with Organizations
e. Market Context: Market Opportunities; Customer Needs; Financial Planning
for New Products
h.
Appendix 4: Kristen Wolfe's Occupation List
Professor
Non-Academic Researcher
Member of the Military
Not currently employed outside the home
Other
Engineer
Technical Manager
Consultant
Doctor
Attorney
40
Appendix 5: Modified Occupation List
(Changes marked with an asterisk*)
Engineer
Manager*
Consultant
Attorney
Professor (College or University)*
Currently Out of the Work Force*
Banking/Finance*
Student*
Doctor
Other
Appendix 6: List of Tasks
Creating or Modifying:
- Designing or conducting performance tests or building testing rigs
-
Writing code
- Conducting analyses of the physics of a product
- Reworking a project decision to compensate for a misunderstanding
- Modifying the design of an existing component
Communicating or Interacting
-
Reading or sending email
-
Responding to requests or questions from others
-
Interviewing candidates
-
Meeting with one or more members of your project team
Meeting with other company employees or organization members
-
Interacting with customers or users
- Communicating with vendors or suppliers
- Planning or organizing a person's or team's activities
Planning or Designing
-
Documenting projects or outcomes
-
Mining previous projects or reports for information
Developing a project strategy or direction
Creating or modifying a CAD representation
-
Planning a code-building cycle
-
Working alone to make project decisions
-
Evaluating competitors' products
Appendix 7: Final Survey
This section serves to show the order and format in which the questions were
asked. The conditional questions for occupation are not shown, but are identical in
format to the occupation questions themselves.
The task list is not shown in full in the screenshot of the survey, but a full list is
provided in Appendix 6. The same goes for the Frequency of Use, Expected
Proficiency, and Source questions; their full list is provided in Appendix 3.
41
Welcome!
Hello and thank you for taking part in this survey examining the careers of the alumni of
the Mechanical Engineering Department at MIT. As an MIT alumnus with experience after
graduation, you can offer insightful information about the skills and knowledge that you
have found most useful (or not useful) in your career. This data will help identify ways in
which the undergraduate curriculum could be modified, and will inform current students
about possible career paths.
The survey is voluntary. Please be assured that the data will be treated as confidential,
and the results of any research or analysis using the data will be presented in a way that
individual respondents cannot be identified. If data from this survey are used for
academic research, the same rules of confidentiality and reporting apply.
Kelly Wang, Class of 2015, Department of Mechanical Engineering
Professor Warren Searing, Department of Mechanical Engineering
What is your current occupation and background?
Please select the option that most closely describes your CURRENT occupation.
Engineer
Manager
Consultant
Banking/Ecnance
Doctor
Attorney
Profes sor 'College or University)
Currently Out of the Work Force
Student
Other
42
Please select the option(s) that most closely describes any degree(s) that you have
received to date in addition to your BS from our department.
N/A
PhD
Masters Degree in Engineering
Law School
Masters of Engineering Management
Medical School
MBA
Other (please specify)
Please select the option that most closely describes your FIRST occupation after
graduating from MIT.
Same as current occupation
Engineer
Manager
Consultant
Out of the Work Force
Student
Other
How many different companies have you been employed at fu-time since you received
your Bachelor of Science degree from MIT?
How many years have you worked at your CURRENT place of employment?
43
What do you spend work time on every week?
Which of these things did you spend more than five hours on lest week?
Planning or Designing
Jocumenting projects or outcomes
3lanning a code-building cycle
Working alone to make project decisons
Creating or modifying a CAD representation
Mning previous projects or reports for information
Evaluat7rg
competitors products
Jeveoping projec- strategy or direction
Nore of the above
How often do you use particular technical knowledge or
skills?
Please select the option to describe how often you use the knowledge or skillsfrom each
category.
TECHNICAL KNOWLEDGE
A -ew
At
Least
At
Least
\ever
T mes
a Year
Orce a
Morth
Underying Sciences
Pthysics; Chemistry Bioogy
o
0
Underlying Mathematics
Cafctus; L ine.r Agebra iffereti
Equarions. Statistics
o
Mechanics of Solids
Forceand Momert Equ,
Mechanical Behavior of Materials
E'asticity; Fracture; Farigue, Piasrcitjy
nibrurn
Conditions of Geometric Fit
rIction, Use of Materials "n
or
Almos-
Once a
Week
On
Most
Days
Everything
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
o
0
0
0
0
0
o
0
0
0
0
0
100
MechanicaI Design
System Dynamics
Dynamic Modeling and Respwnse
System rjrncons;Kinematics of
Bodies in Motion: Frequency
Response; Lnearized Models
44
Where did you gain your knowledge or skills?
Please select the best option to describe where you gained the malority of your
understandina in the following categories. If there is more than one source, please rank
your primary and secondary sources.
Engineering Reasoning
Problem SoMng; Problem Identification;Modeihng; QuantitatIve Analysis
Gracuate
Program
CompanySponsored
Training
Program
Work
Expzerience
Esewnrere
El
1:1
1:1
1:
El
El
1:1
n
El
nl
Unaergracua:e
Program a:
MIT
Primary
Secordary (if
app cable)
Experimentation
Hypothesis Formulation; Experirnental Inquhy; Hypothesis Test and Defense
ULndergracLa3:e
Program a:
Graduate
Drogram
MIT
CompanySporsored
Training
Program
Work
Experience
Elsewvnere
Primary
ElE]
Fl
[]
[]
Secondary (if
app cable)
El
El
El
Ml
Work
Experience
Eisewriere
E
System Thinking
Defining the System and Its Interfaces;Interaction In Systems
Undergracua7e
Program a:
MIT
Graduate
Program
CompanySponsored
Training
Program
Primary
11
[]1
El
II]
E
Secorary (if
applicable)
C-1
F-
El
El
E
How proficient do you need to be in specific areas?
Please select the best option to describe how proficient you are expected to be in the following categories.
To
essentziy
have ro
ktow edge
ot
To Iave
some
expenence
ore
exposure
r
To be aD e
participate
in and
contribLte
To be
able to
innovate
Lrterszand
and explain
To be ski leo in
the practice and
mplemertat on
of
To be able
to
ar teac
in
Indepandent Thinking
Setting Project Goals; Warking
o
0
0
0
0
0
Teamwork
o
o
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0
0
Independeniy
Goal Setting; Scheduling
LeadwShp
Decision Making. Drganization and
Delegation: Negotiation, Ability to
Motivate Others; Risk Management
Comnuiication
Wnflen Multimedia; Graphbral; dnat
Presentation Communication to those
Outsdeof re Field
45
Summing Up
Thank you very much for taking the time to complete this survey. The past questions have
been focused on specific knowledge and skills. We now want to open it up to a broader
scope.
What aspects In your MIT experience have been most valuable for you professionally?
Please list up to three.
2
If applicable, how did your college internships influence your career decision?
Faculty from the MIT Schools of Engineering and Management are considering the
possibility of offering continuing professional education opportunities for alumni, in
formats including online classes, resident short courses, and degree programs. If MIT
were to offer courses such as these, what topics would you like to see included? Please
list up to five topic areas.
1
2
4
Would you be willing to take part in future focus groups that might be set up on the results
of this study? Please indicate your interest by checking yes and entering an email address
where you are best reached. Your contact email will be disconnected from your survey
responses.
Appendix 8: Correspondence Emails
FirstEmail Correspondence:
Email Subject: MIT Study on Careersof MechE Alumni
Dear [name],
As the needs of our Mechanical Engineering undergraduates evolve, we are working to see that our
program keeps pace. To enable us to improve, we need to understand what knowledge is of value to
our alumni and the paths that their careers are taking. We're reaching out to you with the hope that
you will be willing to help us gather this information.
Our goal for this project is to learn about the professional activities of our alumni over their various
careers in order to discern what they do specifically in their jobs. We intend to use this information
to tailor our department's curriculum to reflect the needs of our alumni. Additionally, we want to
share this aggregate knowledge about alumni careers with our current mechanical engineering
undergraduates with hope that consequently they will be able to make more informed decisions
about their own career directions.
You can help us to accomplish this by filling out our career survey.
[unique link]
46
This is a unique link, given only to you, so please do not share it with others or forward this email to
others. This survey should take about 15 minutes to complete, and the information gathered will be
very valuable to us.
We sincerely appreciate your willingness to help.
Warren Seering
Weber-Shaughness Professor of Mechanical Engineering
FirstReminder Email:
Email Subject: Professionalpaths of MIT MechE Alumni
Dear [name],
My name is Kelly Wang, and I am a senior at MIT in the Mechanical Engineering Department. As a
soon-to-be graduate of the institute, I have become increasingly curious about the various
professional paths of our department's alumni, and have therefore decided to focus my thesis on
exactly that. I am working with the department in the hopes to gather information on the
professional skills of our alumni, looking to determine what they do specifically in their jobs and the
knowledge utilized in their careers.
About a week ago, you received an email from Professor Seering with a link for the Mechanical
Engineering Alumni Survey. Fifteen minutes of your time with this survey will help tremendously in
my efforts to provide the department with a better understanding of the professional lives of their
graduates and to collect the data for my thesis.
The questionnaire is available via your personal web link:
[unique link]
Thank you for your help,
Kelly Wang
Second/FinalReminder Email:
Email Subject: Influence the trajectoriesoffuture MIT MechE students
Dear [name],
I'm following up Kelly Wang's recent note, hoping that you will find time in the next few days to
respond to our Course 2 alumni careers survey. Knowledge of the needs of our graduates is most
helpful to us as we consider future program and curricular options.
The information we've received so far is giving us an understanding of the professional lives of our
alumni that we have not had before. Your response will enable us to look more carefully into the
trajectories of each graduating class so that we can understand your professional needs over time.
Your taking 15 minutes (mean 14.96, s.d. 9.94 so far) will be very, very helpful to us in this regard.
We will need your response soon so that Kelly can include your data in her thesis.
Thank you for considering our request. Your responding will be important for us and for future
graduates of our department. Kelly and I sincerely appreciate your help.
Warren Seering
Weber/Shaughness Professor of Mechanical Engineering
Kelly Wang
Class of 2015 (!)
[unique link]
47
Appendix 9: Advanced Degree Responses
Prompt: Please select the option that most closely describes the degree program that you
are enrolled in.
Responses (taken directly from Qualtrics):
Masless Dgee in.
Mastes of go"".
MmuagemeMt
School
Law
Mes-ed-l School
-
Wee
"
00e
is
I
30
21
I# ^no~e
1
6so
4
%
Response
0
0.0%
3
MBA
8
11.1%
4
PhD
39
54.2%
5
Law School
0
0.0%
6
Medical
4
5.6%
7
Other Ilease specifv
3
42%
Total
72
100.0%
-
18
2
Masters Degree in Engineerina
11
Masters of Enqineein Management
School
25.0%
Prompt: Please select the option(s) that most closely describes any degree(s) that you have
received to date in addition to your BS from our department.
Responses (taken directly from Qualtrics):
Mstere Dagresin Engiweeing
Masters
of Engbweefg MonagusmW
I
MBA
PhD
Law
School
Medkal School
speIfy
S
#
106
266
466
366
Response
Answ2r
N/A
Degree in Engineeting
%
Oder (pop6a
I
U
291
40.2%1
263
36.3%
2
Masters
3
Masters of Engineering Managerrvent
4
MBA
76
10.5%
S
PhD
72
9.9%
6
Law School
18
2.5%
7
Medical School
29
4.0%
8
Other (please specify)
54
7.5%
12
48
ADpendix 10: Old 2-A Reauirements
Old 2-A Requirements (for class of 2015 and earlier):
GIRs: Biology, Chemistry, Calculus I & 11, Physics I & II, 8 HASS, REST: 18.03 + 2.001, Lab:
2.671
Communications Requirement: 2 Cl-H, 2 CI-M: 2.671 + 2.009
Departmental Program
Required Departmental Core Subjects
2.001
Mechanics & Materials 1, 12, REST; Physics 1, Calc 11, 18.03
2.003J Dynamics & Control I, 12, REST; Physics I, 18.03
2.005 Thermal-Fluids Engineering I, 12, REST; Physics II, Calc II, 18.03
The Product Engineering Process, 12, CI-M; 2.001, 2.003J, 2.005; 2.00B or 2.670;
2.009
senior standing or permission of instructor
2.670 Mechanical Engineering Tools, 3
2.671 Measurement & Instrumentation, 12, LAB, CI-M; 2.001, 2.003, Physics II
18.03 Differential Equations, 12, REST; 18.02
Two Additional Mechanical Engineering Subjects
2.002 Mechanics & Materials II, 12; 2.001, Chemistry
2.004 Dynamics & Control II, 12; 2.003J, Physics II
2.006 Thermal-Fluids Engineering II, 12; 2.005, 18.03
2.007 Design & Manufacturing 1, 12; 2.001
2.008 Design & Manufacturing II, 12, 1/2 LAB; 2.001; 2.005; 2.007 or 2.017J
2.086 Numerical Computation for Mechanical Engineers, 12; Physics I, Calc II, 18.03
2.ThU Undergraduate Thesis, 12
Elective Subjects with Engineering Content: 72 units (your 2-A concentration)
Unrestricted Electives: 48 units
Total Units Beyond the GIRs Required for SB Degree: 183
References
1) Wolfe, K., 2004, "Understanding the Careers of the Alumni of the MIT
Mechanical Engineering Department," Undergraduate Thesis, Massachusetts
Institute of Technology, Cambridge, MA.
2) Kelly, C., 2003, "Some Trends in the Career Paths Followed by Alumni of the
MIT Mechanical Engineering Department," Undergraduate Thesis,
Massachusetts Institute of Technology, Cambridge, MA.
3) Batra, N., 2010, ""A Look to the Future: MIT Alumni and their Course 2 and 2A Educational Experience," Undergraduate Thesis, Massachusetts Institute of
Technology, Cambridge, MA.
49